von Petros Christopoulos ; Martina Kirchner ; Farastuk Bozorgmehr ; Nikolaus Magios ; Daniel Kazdal ; Anna-Lena Volckmar ; Lena Marie Brückner ; Tilmann Bochtler ; Mark Kriegsmann ; Volker Endris ; Roland Penzel ; Katharina Kriegsmann ; Martin E. Eichhorn ; Felix Herth ; Claus Peter Heußel ; Rami El-Shafie ; Marc Schneider ; Thomas Muley ; Michael Meister ; Peter Schirmacher ; Helge Bischoff ; Frank Griesinger ; Albrecht Stenzinger ; Michael Thomas
Objective - Panel-based next-generation sequencing (NGS) is increasingly used for the diagnosis of EGFR-mutated non-small-cell lung cancer (NSCLC) and could improve risk assessment in combination with clinical parameters. - Materials and methods - To this end, we retrospectively analyzed the outcome of 400 tyrosine kinase inhibitor (TKI)-treated EGFR+ NSCLC patients with validation of results in an independent cohort (n = 130). - Results - EGFR alterations other than exon 19 deletions (non-del19), TP53 co-mutations, and brain metastases at baseline showed independent associations of similar strengths with progression-free (PFS hazard ratios [HR] 2.1-2.3) and overall survival (OS HR 1.7-2.2), in combination defining patient subgroups with distinct outcome (EGFR+ NSCLC risk Score, "ENS", p < 0.001). Co-mutations beyond TP53 were rarely detected by our multigene panel (<5%) and not associated with clinical endpoints. Smoking did not affect outcome independently, but was associated with non-del19 EGFR mutations (p < 0.05) and comorbidities (p < 0.001). Laboratory parameters, like the blood lymphocyte-to-neutrophil ratio and serum LDH, correlated with the metastatic pattern (p < 0.01), but had no independent prognostic value. Reduced ECOG performance status (PS) was associated with comorbidities (p < 0.05) and shorter OS (p < 0.05), but preserved TKI efficacy. Non-adenocarcinoma histology was also associated with shorter OS (p < 0.05), but rare (2-3 %). The ECOG PS and non-adenocarcinoma histology could not be validated in our independent cohort, and did not increase the range of prognostication alongside the ENS. - Conclusions - EGFR variant, TP53 status and brain metastases predict TKI efficacy and survival in EGFR+ NSCLC irrespective of other currently available parameters ("ENS"). Together, they constitute a practical and reproducible approach for risk stratification of newly diagnosed metastatic EGFR+ NSCLC.
Lung cancer Amsterdam [u.a.] : Elsevier, 1985 148(2020), Seite 105-112 Online-Ressource
von David Capper ; David T. W. Jones ; Daniel Schrimpf ; Dominik Sturm ; Christian Kölsche ; Felix Sahm ; David Reuss ; Annekathrin Kratz ; Annika K. Wefers ; Kristin Huang ; Kristian Wilfried Pajtler ; Leonille Schweizer ; Damian Stichel ; Florian Selt ; Hendrik Witt ; Till Milde ; Olaf Witt ; Wolfram Scheurlen ; Christoph Geisenberger ; Stefanie Brehmer ; Marcel Seiz-Rosenhagen ; Daniel Hänggi ; Andreas Kulozik ; Axel Benner ; Martin Bendszus ; Jürgen Debus ; Michael Platten ; Andreas Unterberg ; Wolfgang Wick ; Marcel Kool ; Christel Herold-Mende ; Andreas von Deimling ; Stefan Pfister ; Hermann L. Müller
Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging—with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
Nature London [u.a.] : Nature Publ. Group, 1869 555(2018), 7697, Seite 469-474 Online-Ressource
von Michael Kreuter ; Johan F. Vansteenkiste ; Jürgen Fischer ; Wilfried E. E. Eberhardt ; Heike Zabeck ; Jens Kollmeier ; Monika Serke ; Norbert Frickhofen ; Martin Reck ; Walburga Engel-Riedel ; Silke Neumann ; Michiel Thomeer ; Christian Schumann ; Paul De Leyn ; Thomas Graeter ; Georgios Stamatis ; Frank Griesinger ; Michael Thomas
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